An analytic narrative of Caesar’s death: Suicide or not? That is the question

2018 ◽  
Vol 30 (3) ◽  
pp. 332-349 ◽  
Author(s):  
Bertrand Crettez ◽  
Régis Deloche

On the Ides of March, 44 BC, in the Senate House of Pompey in Rome, Julius Caesar was assassinated by conspirators, the most famous of those being Brutus. Are there objectively valid reasons to confirm the possibility of a suicidal wish on the part of Caesar raised by Suetonius? By building and solving a two-player non-cooperative game that models the historical strategic aspects of the relationship between Caesar and Brutus, our article shows that there is no need to subscribe to the suicide thesis to explain Caesar’s death. We formulate our conclusion via the solution concept of mixed-strategy Nash equilibrium.

2014 ◽  
Vol 494-495 ◽  
pp. 1102-1105
Author(s):  
Xia Chen ◽  
Yi Fei Wang

Multiple unmanned aerial vehicles (UAV) cooperative alliance combat is a new research problem. Through considering cooperative alliance's target value income index function, damage cost index function and voyage cost index function, the multi-UAV alliance cooperative game model is established in the paper, and its game matrix is structured. The definition of alliance characteristic function and mixed strategy Nash equilibrium are provided, the mixed strategy Nash equilibrium is obtained by using particle swarm optimization, and the cooperative game is solved by applying the method. At last, the feasibility and effectiveness of the method are presented by simulation results.


2019 ◽  
Vol 9 (20) ◽  
pp. 4395 ◽  
Author(s):  
Weisheng Liu ◽  
Jian Wu ◽  
Fei Wang ◽  
Yixin Huang ◽  
Qiongdan Dai ◽  
...  

The increasing penetration of distributed generation (DG) brings about great fluctuation and uncertainty in distribution networks. In order to improve the ability of distribution networks to cope with disturbances caused by uncertainties and to evaluate the maximum accommodation capacity of DG, a multi-objective programming method for evaluation of the accommodation capacity of distribution networks for DG is proposed, considering the flexibility of distribution networks in this paper. Firstly, a multi-objective optimization model for determining the maximum accommodation of DG by considering the flexibility of distribution networks is constructed, aiming at maximizing the daily energy consumption, minimizing the voltage amplitude deviation, and maximizing the line capacity margin. Secondly, the comprehensive learning particle swarm optimization (CLPSO) algorithm is used to solve the multi-objective optimization model. Then, the mixed strategy Nash equilibrium is introduced to obtain the frontier solution with the optimal joint equilibrium value in the Pareto solution set. Finally, the effectiveness of the proposed method is demonstrated with an actual distribution network in China. The simulation results show that the proposed planning method can effectively find the Pareto optimal solution set by considering multiple objectives, and can obtain the optimal equilibrium solution for DG accommodation capacity and distribution network flexibility.


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